
"""simple docstring"""


from __future__ import annotations

import math






def    _snake_case					(		snake_case__ :  Dict  ):



	if 1 < number < 4:
		# 2 and 3 are primes
		return True
	elif number < 2 or number % 2 == 0 or number % 3 == 0:
		# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
		return False

	# All primes number are in format of 6k +/- 1
	for i in range(5						,   int(math.sqrt(a__  ) + 1  )						,   6  ):
		if number % i == 0 or number % (i + 2) == 0:
			return False
	return True






def    _snake_case					(		snake_case__ :  str  ):
	A     = str(a__  )
	A     = [n]
	for i in range(1						,   len(a__  )  ):
		list_nums.append(int(str_num[i:]  )  )
		list_nums.append(int(str_num[:-i]  )  )
	return list_nums






def    _snake_case					(		snake_case__ :  str  ):



	if len(str(a__  )  ) > 3:
		if not is_prime(int(str(a__  )[-3:]  )  ) or not is_prime(int(str(a__  )[:3]  )  ):
			return False
	return True






def    _snake_case					(		snake_case__ :  Any = 11  ):
	A     = []
	A     = 13
	while len(a__  ) != count:
		if validate(a__  ):
			A     = list_truncated_nums(a__  )
			if all(is_prime(a__  ) for i in list_nums  ):
				list_truncated_primes.append(a__  )
		num += 2
	return list_truncated_primes






def    _snake_case					(		):
	return sum(compute_truncated_primes(11  )  )


if __name__ == "__main__":
		print(F"""{sum(compute_truncated_primes(11)) = }""")


from ...configuration_utils import PretrainedConfig
from ...utils import logging


__snake_case				:      Any   		=			logging.get_logger(__name__)

__snake_case				:      Union[str, Any]   		=			{
    """microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
    # See all Cvt models at https://huggingface.co/models?filter=cvt
}



class        A__(a_							):
						"""simple docstring"""






						_A    :				Union[str, Any]       					=			'''cvt'''





						def __init__(    self  ,      _lowercase=3  ,      _lowercase=[7, 3, 3]  ,      _lowercase=[4, 2, 2]  ,      _lowercase=[2, 1, 1]  ,      _lowercase=[64, 192, 384]  ,      _lowercase=[1, 3, 6]  ,      _lowercase=[1, 2, 10]  ,      _lowercase=[4.0, 4.0, 4.0]  ,      _lowercase=[0.0, 0.0, 0.0]  ,      _lowercase=[0.0, 0.0, 0.0]  ,      _lowercase=[0.0, 0.0, 0.1]  ,      _lowercase=[True, True, True]  ,      _lowercase=[False, False, True]  ,      _lowercase=["dw_bn", "dw_bn", "dw_bn"]  ,      _lowercase=[3, 3, 3]  ,      _lowercase=[1, 1, 1]  ,      _lowercase=[2, 2, 2]  ,      _lowercase=[1, 1, 1]  ,      _lowercase=[1, 1, 1]  ,      _lowercase=0.0_2  ,      _lowercase=1e-12  ,      **_lowercase  ,      )     -> Tuple:
									super().__init__(**_lowercase    )
									a_						:						str 							= num_channels
									a_						:						Optional[int] 							= patch_sizes
									a_						:						Dict 							= patch_stride
									a_						:						int 							= patch_padding
									a_						:						int 							= embed_dim
									a_						:						Tuple 							= num_heads
									a_						:						Optional[Any] 							= depth
									a_						:						str 							= mlp_ratio
									a_						:						Optional[int] 							= attention_drop_rate
									a_						:						int 							= drop_rate
									a_						:						List[Any] 							= drop_path_rate
									a_						:						List[Any] 							= qkv_bias
									a_						:						Dict 							= cls_token
									a_						:						Union[str, Any] 							= qkv_projection_method
									a_						:						List[Any] 							= kernel_qkv
									a_						:						Optional[Any] 							= padding_kv
									a_						:						Any 							= stride_kv
									a_						:						Dict 							= padding_q
									a_						:						Optional[int] 							= stride_q
									a_						:						Tuple 							= initializer_range
									a_						:						int 							= layer_norm_eps


